Extraction of structure of medical diagnosis from clinical data

Authors:
Shusaku Tsumoto
Affiliations:
Department of Medical Informatics, Shimane University, School of Medicine, 89-1 Enya-cho Izumo City, Shimane 693-8501 Japan
Venue:
Fundamenta Informaticae - Special issue on the 9th international conference on rough sets, fuzzy sets, data mining and granular computing (RSFDGrC 2003)
Year:
2003

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Abstract

One of the most important problems with rule induction methods is that they cannot extract rules, which plausibly represent expert decision processes. In this paper, the characteristics of experts' rules are closely examined and a new approach to extract plausible rules is introduced, which consists of the following three procedures. First, the characterization of decision attributes (given classes) is extracted from databases and the concept hierarchy for given classes is calculated. Second, based on the hierarchy, rules for each hierarchical level are induced from data. Then, for each given class, rules for all the hierarchical levels are integrated into one rule. The proposed method was evaluated on a medical database, the experimental results of which show that induced rules correctly represent experts' decision processes.